Client Report - [Insert Project Title]

Course DS 250

Author

[Tanner Hamblin]

Show the code 
import pandas as pd
import numpy as np
from lets_plot import *

LetsPlot.setup_html(isolated_frame=True)

Project Notes

For Project 1 the answer to each question should include a chart and a written response. The years labels on your charts should not include a comma. At least two of your charts must include reference marks.

Show the code 
# Learn morea about Code Cells: https://quarto.org/docs/reference/cells/cells-jupyter.html

# Include and execute your code here
df = pd.read_csv("https://raw.githubusercontent.com/byuidatascience/data4names/master/data-raw/names_year/names_year.csv")

QUESTION|TASK 1

How does your name at your birth year compare to its use historically?

type your results and analysis here

Show the code 
df.head()
df_Tanner = df.query("name == 'Tanner'")
df_Tanner.head()
print(df_Tanner.dtypes)
name      object
year       int64
AK       float64
AL       float64
AR       float64
AZ       float64
CA       float64
CO       float64
CT       float64
DC       float64
DE       float64
FL       float64
GA       float64
HI       float64
IA       float64
ID       float64
IL       float64
IN       float64
KS       float64
KY       float64
LA       float64
MA       float64
MD       float64
ME       float64
MI       float64
MN       float64
MO       float64
MS       float64
MT       float64
NC       float64
ND       float64
NE       float64
NH       float64
NJ       float64
NM       float64
NV       float64
NY       float64
OH       float64
OK       float64
OR       float64
PA       float64
RI       float64
SC       float64
SD       float64
TN       float64
TX       float64
UT       float64
VA       float64
VT       float64
WA       float64
WI       float64
WV       float64
WY       float64
Total    float64
dtype: object
Show the code 
(
  ggplot(df_Tanner, aes(x = 'year', y = 'Total')) + 
geom_line() +
labs(
  x = "Year",
  title = "Tanner is becoming less popular"
) +
geom_vline(xintercept = "2002", color = "red") +
  theme_bw() +
  geom_text(aes(x=[2001], y=[15], label=["Year I was born"]), size=8, color='red',hjust = 1)


)



# print("Hello")

QUESTION|TASK 2

If you talked to someone named Brittany on the phone, what is your guess of his or her age? What ages would you not guess?

type your results and analysis here

Show the code 
df_Brittany = df.query("name == 'Brittany'") 
df_Brittany.head()
name year AK AL AR AZ CA CO CT DC ... TN TX UT VA VT WA WI WV WY Total
53205 Brittany 1968 0.0 0.0 0.0 0.0 5.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.0
53206 Brittany 1969 0.0 0.0 0.0 0.0 7.0 0.0 0.0 0.0 ... 0.0 5.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 12.0
53207 Brittany 1970 0.0 0.0 0.0 0.0 5.0 5.0 0.0 0.0 ... 0.0 7.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 32.0
53208 Brittany 1971 0.0 0.0 0.0 5.0 17.0 0.0 0.0 0.0 ... 0.0 14.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 81.0
53209 Brittany 1972 0.0 0.0 0.0 0.0 11.0 10.0 0.0 0.0 ... 8.0 14.0 16.0 0.0 0.0 0.0 5.0 0.0 0.0 158.0

5 rows × 54 columns

Show the code 
(ggplot(df_Brittany, aes(x = "year", y = "Total")) +
  geom_line() +
  geom_vline(xintercept=1990, linetype=2, color='red', alpha=0.5) +
  labs(title = "Most Brittanys born in 1990" , x = "Year"
  
  )
  
  
  )

QUESTION|TASK 3

Mary, Martha, Peter, and Paul are all Christian names. From 1920 - 2000, compare the name usage of each of the four names in a single chart. What trends do you notice?

type your results and analysis here

Show the code 
# names =
df_bible = df.query("name in ['Mary', 'Martha', 'Peter', 'Paul']")
Show the code 
(ggplot(df_bible, aes( x = "year", y = "Total", color = "name")) +
  # geom_jitter() +
  geom_line() +
  scale_color_manual(values=["red","blue","green","yellow"]) +
  labs(title = "Biblical names are becoming less popular") +
  theme_bw()

)

QUESTION|TASK 4

Think of a unique name from a famous movie. Plot the usage of that name and see how changes line up with the movie release. Does it look like the movie had an effect on usage?

type your results and analysis here

Show the code 
df_Anakin = df.query("name == 'Anakin'")
df_Anakin.head()
name year AK AL AR AZ CA CO CT DC ... TN TX UT VA VT WA WI WV WY Total
19325 Anakin 1998 0.0 0.0 0.0 0.0 5.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.0
19326 Anakin 1999 0.0 0.0 0.0 9.0 19.0 0.0 0.0 0.0 ... 0.0 15.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 61.0
19327 Anakin 2000 0.0 0.0 0.0 0.0 8.0 6.0 0.0 0.0 ... 0.0 12.0 0.0 0.0 0.0 5.0 0.0 0.0 0.0 44.0
19328 Anakin 2001 0.0 0.0 0.0 0.0 8.0 0.0 0.0 0.0 ... 0.0 7.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 15.0
19329 Anakin 2002 0.0 0.0 0.0 0.0 9.0 0.0 0.0 0.0 ... 0.0 8.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 17.0

5 rows × 54 columns

Show the code 
(ggplot(df_Anakin, aes(x = "year", y = "Total")) +
geom_line() +
labs(title = "Anakin is getting more popular", x = "Years") +
geom_vline(xintercept = "1999", color = "darkgreen") +
geom_vline(xintercept = "2002", color = "blue") +
geom_vline(xintercept = "2005", color = "red") +
geom_text(aes(x=[1999], y=[65], label=["Episode I"]), size=8, color='darkgreen',hjust = 0) +
geom_text(aes(x=[2002], y=[25], label=["Episode II"]), size=8, color='blue',hjust = 0) +
geom_text(aes(x=[2005], y=[100], label=["Episode III"]), size=8, color='red',hjust = 0)

)

STRETCH QUESTION|TASK 1

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